An automated version of the operation span task.

School of Psychology, Georgia Institute of Technology, Atlanta, Georgia 30332-0170, USA.
Behavior Research Methods (Impact Factor: 2.12). 09/2005; 37(3):498-505. DOI: 10.3758/BF03192720
Source: PubMed

ABSTRACT We present an easy-to-administer and automated version of a popular working memory (WM) capacity task (operation span; Ospan) that is mouse driven, scores itself, and requires little intervention on the part of the experimenter. It is shown that this version of Ospan correlates well with other measures of WM capacity and has both good internal consistency (alpha = .78) and test-retest reliability (.83). In addition, the automated version of Ospan (Aospan) was shown to load on the same factor as two other WM measures. This WM capacity factor correlated with a factor composed of fluid abilities measures. The utility of the Aospan was further demonstrated by analyzing response times (RTs) that indicated that RT measures obtained in the task accounted for additional variance in predicting fluid abilities. Our results suggest that Aospan is a reliable and valid indicator of WM capacity that can be applied to a wide array of research domains.

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    ABSTRACT: Transfer of trained skill was investigated from the viewpoint of mental resources. Participants alternated between a simple training task and a complex task, the video game Everyday Shooter. The training tasks, occlusions and visual words (Boles, 1991, 1992, 1996), shared many critical resources, or few resources, respectively, with the video game. Also, participants received standard task-specific instructions or stand-ard instructions along with additional metacognitive instructions on similarities between the training task and video game. Bidirectional transfer was noted for those training the occlusions task and receiving stand-ard instructions, demonstrating the value of resource training with an alternating design, even when the target task is a complex one. There is a need to understand how to maximize skill de-velopment when training operators to undertake vital opera-tional assignments such as flying aircraft. At present, there is debate over how to best train operators and achieve skill trans-fer, such as whether performance improvements can only be realized by training with the target task or if improvements can be realized by training with a different task. Transfer of training. Transfer of training occurs when in-formation learned in one environment assists performance in another environment. Although the topic of transfer has been breached before (e.g., Thorndike & Woodworth, 1901; Halpern, 1998; Brown, 1989), few have examined transfer on a cognitive level from the viewpoint of mental resources. Near transfer occurs when knowledge acquired within one context is applied to a similar target task within a similar con-text (Barnett & Ceci, 2002). However this is not the only form of transfer. Boles (1997) suggested that successful transfer can occur even if a training task is different from a target task, as long as the training task provides practice with the mental re-sources critical to the target task. Transfer from one context to a dissimilar context is referred to as far transfer (Barnett & Ceci, 2002). Boles (1997) provides evidence that practicing one task drawing upon a spatial quantitative cognitive re-source may transfer to another task drawing upon the same spatial quantitative cognitive resource. Since the two tasks contain different stimuli and require different judgments, this is evidence of transfer at the cognitive level. Recent efforts have sought to determine if transfer occurs when more com-plex cognitive tasks are used (e.g., Phillips, 2007). Studies from various domains have found evidence that the effects of training can be transferred between unrelated tasks (e.g., Brown, 1989; Gick & Holyoak, 1983), but this has not been consistently demonstrated. Boles (2009) failed to find evidence of transfer between video games sharing cognitive resources. The similarity of the cognitive resources being used by the games was assessed with the Multiple Resources Ques-tionnaire (MRQ; Boles & Adair, 2001a, b). Since two of the games required the use of similar cognitive resources, it was hypothesized that playing one would lead to a higher score on the other. This hypothesis was not supported. However, Phil-lips (2007) found a marginally significant trend to suggest that transfer occurred between a simple computer task and a more complex video game, suggesting that it is possible for skills learned on a simple task to transfer to a dissimilar complex task via resource training. One approach to training is for the training task to mirror the target task (Carlson, Khoo, & Elliot, 1990; Briggs & Brogden, 1954). Hawkins & Orlady (1993) suggest that high fidelity training environments can actually take away from training if the target task is not emulated consistently, and Robinson and Mania (2007) claim information uptake is what matters rather than a recreation of the target task. They claim that many physics simulations do not simulate environments that accurately cause users to draw upon behavior, cognition, or perceptual processes that the target task uses. However, training with closely related tasks is not the only way to train. Part-task training involves breaking down a complex tar-get task into subcomponents that can be practiced in isolation, and is capable of producing performance gains (Gopher, Weil, & Bareket, 1994; Whaley & Fisk, 1993; Wightman & Lintern, 1985). Wickens and Hollands (2001) detailed the process to fractionalize a complex task. 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The tasks employed in resource training are generally simpler than high-fidelity simulations, cheaper, and often run on easily obtained computers and video game consoles; thus reducing cost and making training more accessible.
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    Frontiers in Psychology 11/2014; 5:1360. · 2.80 Impact Factor

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Richard Philip Heitz